Distributed storage network with replication control and methods for use therewith

ABSTRACT

A method includes encoding input data into a plurality of slices. The plurality of slices are sent to a first plurality of distributed storage and task execution units for storage, the first plurality of distributed storage and task execution units being located at a corresponding first plurality of sites. Write slice data is received from the first plurality of distributed storage and task execution units. The method determines when replication is to be applied to the plurality of slices. When replication is to be applied to the plurality of slices, a second plurality of distributed storage and task execution units are selected, a plurality of replicated slices corresponding to the plurality of slices are generated, and the plurality of replicated slices are sent to the second plurality of distributed storage and task execution units.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) system in accordance with the present invention;

FIG. 40B is a flowchart illustrating an example of identifying alternatestorage in accordance with the present invention;

FIG. 41A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentinvention;

FIG. 41B is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentinvention;

FIG. 41C is a flowchart illustrating an example of replicating encodeddata slices in accordance with the present invention;

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of coordinating taskexecution in accordance with the present invention;

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentinvention;

FIG. 43B is a flowchart illustrating an example of accessing data inaccordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system in accordance with the present invention;

FIG. 44B is a diagram illustrating an example of a migration of virtualstorage units within physical storage units in accordance with thepresent invention;

FIG. 44C is a flowchart illustrating an example of commissioning storageunits in accordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system in accordance with the presentinvention;

FIG. 45B is a timing diagram illustrating an example of accessperformance in accordance with the present invention;

FIG. 45C is a flowchart illustrating an example of prioritizing accessrates in accordance with the present invention;

FIG. 46A is a diagram illustrating an example of modifying scoringinformation in accordance with the present invention;

FIG. 46B is a diagram illustrating another example of modifying scoringinformation in accordance with the present invention;

FIG. 46C is a flowchart illustrating an example of updating scoringinformation in accordance with the present invention;

FIG. 47A is a diagram illustrating another example of modifying scoringinformation in accordance with the present invention;

FIG. 47B is a flowchart illustrating another example of updating scoringinformation in accordance with the present invention;

FIG. 48 is a flowchart illustrating another example of updating scoringinformation in accordance with the present invention; and

FIG. 49 is a flowchart illustrating another example of updating scoringinformation in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interfaces 30support a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing module 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terabytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terabytes) into 100,000 data segments, each being 1 Gigabyte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the group selecting modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the first set of encoded data slices include errorcorrection data based on the first-third words of the first datasegment. With such an encoding and slicing scheme, retrieving any threeof the five encoded data slices allows the data segment to be accuratelyreconstructed.

The encoding and slices of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_(—)1and ES1_(—)2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selection module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selection module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_(—)1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_(—)2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_(—)3) is sent to the fourth DST execution unit; the fourth slicegrouping of the second data partition (e.g., slice group 2_(—)4, whichincludes first error coding information) is sent to the fifth DSTexecution unit; and the fifth slice grouping of the second datapartition (e.g., slice group 2_(—)5, which includes second error codinginformation) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 andthe memory 88. For example, when the partial task 98 includes aretrieval request, the controller 86 outputs the memory control 174 tothe memory 88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step executing the task in accordance with the task controlinformation 176, the DT execution module 90 retrieves the encoded slicesfrom memory 88. The DT execution module 90 then reconstructs contiguousdata blocks of a data partition. As shown for this example,reconstructed contiguous data blocks of data partition 1 include datablocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieve slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_(—)1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of a de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distributions modules location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few Terabytes or more),addressing information of Addr_(—)1_AA, and DS parameters of ⅗;SEG_(—)1; and SLC_(—)1. In this example, the addressing information maybe a virtual address corresponding to the virtual address of the firststorage word (e.g., one or more bytes) of the data and information onhow to calculate the other addresses, may be a range of virtualaddresses for the storage words of the data, physical addresses of thefirst storage word or the storage words of the data, may be a list ofslice names of the encoded data slices of the data, etc. The DSparameters may include identity of an error encoding scheme, decodethreshold/pillar width (e.g., ⅗ for the first data entry), segmentsecurity information (e.g., SEG_(—)1), per slice security information(e.g., SLC_(—)1), and/or any other information regarding how the datawas encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_(—)2_XY, andDS parameters of ⅗; SEG_(—)2; and SLC_(—)2. In this example, theaddressing information may be a virtual address corresponding to thevirtual address of the first storage word (e.g., one or more bytes) ofthe task and information on how to calculate the other addresses, may bea range of virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., ⅗ for the first data entry),segment security information (e.g., SEG_(—)2), per slice securityinformation (e.g., SLC_(—)2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_(—)1, 1_(—)2, and 1_(—)3). The DT execution capabilities field280 includes identity of the capabilities of the corresponding DTexecution unit. For example, DT execution module 1_(—)1 includescapabilities X, where X includes one or more of MIPS capabilities,processing resources (e.g., quantity and capability of microprocessors,CPUs, digital signal processors, co-processor, microcontrollers,arithmetic logic circuitry, and/or any other analog and/or digitalprocessing circuitry), availability of the processing resources, memoryinformation (e.g., type, size, availability, etc.), and/or anyinformation germane to executing one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_(—)1—identifynon-words (non-ordered); task 1_(—)2—identify unique words(non-ordered); task 1_(—)3—translate (non-ordered); task1_(—)4—translate back (ordered after task 1_(—)3); task 1_(—)5—compareto ID errors (ordered after task 1-4); task 1_(—)6—determine non-wordtranslation errors (ordered after task 1_(—)5 and 1_(—)1); and task1_(—)7—determine correct translations (ordered after 1_(—)5 and 1_(—)2).The sub-task further indicates whether they are an ordered task (i.e.,are dependent on the outcome of another task) or non-order (i.e., areindependent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_(—)1 translate; andtask 3_(—)2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_(—)2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases. The translated data 282 is translatedback 308 (e.g., sub-task 1_(—)4) into the language of the original datato produce re-translated data 284. These two tasks are dependent on thetranslate task (e.g., task 1_(—)3) and thus must be ordered after thetranslation task, which may be in a pipelined ordering or a serialordering. The re-translated data 284 is then compared 310 with theoriginal data 92 to find words and/or phrases that did not translate(one way and/or the other) properly to produce a list of incorrectlytranslated words 294. As such, the comparing task (e.g., sub-task1_(—)5) 310 is ordered after the translation 306 and re-translationtasks 308 (e.g., sub-tasks 1_(—)3 and 1_(—)4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of ⅗ for their decode threshold/pillar width; hence spanningthe memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done the by DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_(—)1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_(—)1 (e.g., identify non-words on the data) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1. For instance, DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 search for non-wordsin data partitions 2_(—)1 through 2_z to produce task 1_(—)1intermediate results (R1-1, which is a list of non-words). Task 1_(—)2(e.g., identify unique words) has similar task execution information astask 1_(—)1 to produce task 1_(—)2 intermediate results (R1-2, which isthe list of unique words).

Task 1_(—)3 (e.g., translate) includes task execution information asbeing non-ordered (i.e., is independent), having DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate data partitions2_(—)1 through 2_(—)4 and having DT execution modules 1_(—)2, 2_(—)2,3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5 through 2_zto produce task 1_(—)3 intermediate results (R1-3, which is thetranslated data). In this example, the data partitions are grouped,where different sets of DT execution modules perform a distributedsub-task (or task) on each data partition group, which allows forfurther parallel processing.

Task 1_(—)4 (e.g., translate back) is ordered after task 1_(—)3 and isto be executed on task 1_(—)3's intermediate result (e.g., R1-3_(—)1)(e.g., the translated data). DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back task 1_(—)3intermediate result partitions R1-3_(—)1 through R1-3_(—)4 and DTexecution modules 1_(—)2, 2_(—)2, 6_(—)1, 7_(—)1, and 7_(—)2 areallocated to translate back task 1_(—)3 intermediate result partitionsR1-3_(—)5 through R1-3_z to produce task 1-4 intermediate results (R1-4,which is the translated back data).

Task 1_(—)5 (e.g., compare data and translated data to identifytranslation errors) is ordered after task 1_(—)4 and is to be executedon task 1_(—)4's intermediate results (R4-1) and on the data. DTexecution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 areallocated to compare the data partitions (2_(—)1 through 2_z) withpartitions of task 1-4 intermediate results partitions R1-4_(—)1 throughR1-4_z to produce task 1_(—)5 intermediate results (R1-5, which is thelist words translated incorrectly).

Task 1_(—)6 (e.g., determine non-word translation errors) is orderedafter tasks 1_(—)1 and 1_(—)5 and is to be executed on tasks 1_(—)1'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 are allocated to compare thepartitions of task 1_(—)1 intermediate results (R1-1_(—)1 throughR1-1_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)6 intermediate results(R1-6, which is the list translation errors due to non-words).

Task 1_(—)7 (e.g., determine words correctly translated) is orderedafter tasks 1_(—)2 and 1_(—)5 and is to be executed on tasks 1_(—)2'sand 1_(—)5's intermediate results (R1-1 and R1-5). DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 are allocated to compare thepartitions of task 1_(—)2 intermediate results (R1-2_(—)1 throughR1-2_z) with partitions of task 1-5 intermediate results partitions(R1-5_(—)1 through R1-5_z) to produce task 1_(—)7 intermediate results(R1-7, which is the list of correctly translated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_(—)1 through 2_z by DT execution modules3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1. For instance, DT executionmodules 3_(—)1, 4_(—)1, 5_(—)1, 6_(—)1, and 7_(—)1 search for specificwords and/or phrases in data partitions 2_(—)1 through 2_z to producetask 2 intermediate results (R2, which is a list of specific wordsand/or phrases).

Task 3_(—)2 (e.g., find specific translated words and/or phrases) isordered after task 1_(—)3 (e.g., translate) is to be performed onpartitions R1-3_(—)1 through R1-3_z by DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2. For instance, DT execution modules1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 search for specifictranslated words and/or phrases in the partitions of the translated data(R1-3_(—)1 through R1-3_z) to produce task 3_(—)2 intermediate results(R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_(—)1), DST unit 1 isresponsible for overseeing execution of the task 1_(—)1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DSTN) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 per the DST allocationinformation of FIG. 32) executes task 1_(—)1 to produce a first partialresult 102 of non-words found in the first data partition. The secondset of DT execution modules (e.g., 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and5_(—)1 per the DST allocation information of FIG. 32) executes task1_(—)1 to produce a second partial result 102 of non-words found in thesecond data partition. The sets of DT execution modules (as per the DSTallocation information) perform task 1_(—)1 on the data partitions untilthe “z” set of DT execution modules performs task 1_(—)1 on the “zth”data partition to produce a “zth” partial result 102 of non-words foundin the “zth” data partition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_(—)1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g.,R1-1_(—)1 through R1-1_m). If the first intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_(—)2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)2in accordance with the DST allocation information. From data partitionto data partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_(—)2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_(—)2 to produce the second intermediate result (R1-2),which is a list of unique words found in the data 92. The processingmodule of DST execution 1 is engaged to aggregate the first through“zth” partial results of unique words to produce the second intermediateresult. The processing module stores the second intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g.,R1-2_(—)1 through R1-2 m). If the second intermediate result is not ofsufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_(—)3 (e.g., translate)on the data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task1_(—)1 if the partitioning is the same. For each data partition, theDSTN identifies a set of its DT execution modules to perform task 1_(—)3in accordance with the DST allocation information (e.g., DT executionmodules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1 translate datapartitions 2_(—)1 through 2_(—)4 and DT execution modules 1_(—)2,2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2 translate data partitions 2_(—)5through 2_z). For the data partitions, the allocated set of DT executionmodules 90 executes task 1_(—)3 to produce partial results 102 (e.g.,1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g.,R1-3_(—)1 through R1-3_y). For each partition of the third intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task1_(—)4 (e.g., retranslate) on the translated data of the thirdintermediate result. To begin, the DSTN module accesses the translateddata (from the scratchpad memory or from the intermediate result memoryand decodes it) and partitions it into a plurality of partitions inaccordance with the DST allocation information. For each partition ofthe third intermediate result, the DSTN identifies a set of its DTexecution modules 90 to perform task 1_(—)4 in accordance with the DSTallocation information (e.g., DT execution modules 1_(—)1, 2_(—)1,3_(—)1, 4_(—)1, and 5_(—)1 are allocated to translate back partitionsR1-3_(—)1 through R1-3_(—)4 and DT execution modules 1_(—)2, 2_(—)2,6_(—)1, 7_(—)1, and 7_(—)2 are allocated to translate back partitionsR1-3_(—)5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_(—)4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_(—)1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes ⅗ decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_(—)5 (e.g., compare) on data 92 and retranslated dataof FIG. 35. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions in accordance with the DSTallocation information or it may use the data partitions of task 1_(—)1if the partitioning is the same. The DSTN module also accesses theretranslated data from the scratchpad memory, or from the intermediateresult memory and decodes it, and partitions it into a plurality ofpartitions in accordance with the DST allocation information. The numberof partitions of the retranslated data corresponds to the number ofpartitions of the data.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_(—)5 in accordance with the DST allocationinformation (e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1,and 5_(—)1). For each pair of partitions, the allocated set of DTexecution modules executes task 1_(—)5 to produce partial results 102(e.g., 1^(st) through “zth”) of a list of incorrectly translated wordsand/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_(—)5 to produce the fifth intermediate result (R1-5), which isthe list of incorrectly translated words and/or phrases. In particular,the processing module of DST execution 1 is engaged to aggregate thefirst through “zth” partial results of the list of incorrectlytranslated words and/or phrases to produce the fifth intermediateresult. The processing module stores the fifth intermediate result asnon-DS error encoded data in the scratchpad memory or in another sectionof memory of DST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_(—)1 through R1-5_z).For each partition of the fifth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task1_(—)6 (e.g., translation errors due to non-words) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of non-words (e.g., the firstintermediate result R1-1). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)6 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)1, 2_(—)1, 3_(—)1, 4_(—)1, and 5_(—)1).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)6 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of incorrectly translated words and/or phrasesdue to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_(—)6 to produce the sixth intermediate result (R1-6), which isthe list of incorrectly translated words and/or phrases due tonon-words. In particular, the processing module of DST execution 2 isengaged to aggregate the first through “zth” partial results of the listof incorrectly translated words and/or phrases due to non-words toproduce the sixth intermediate result. The processing module stores thesixth intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_(—)1 through R1-6_z).For each partition of the sixth intermediate result, the DST clientmodule uses the DS error encoding parameters of the data (e.g., DSparameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_(—)7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_(—)1 and partitionR1-5_(—)1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_(—)7 in accordance with the DST allocation information(e.g., DT execution modules 1_(—)2, 2_(—)2, 3_(—)2, 4_(—)2, and 5_(—)2).For each pair of partitions, the allocated set of DT execution modulesexecutes task 1_(—)7 to produce partial results 102 (e.g., 1^(st)through “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_(—)7 to produce the seventh intermediate result (R1-7), which isthe list of correctly translated words and/or phrases. In particular,the processing module of DST execution 3 is engaged to aggregate thefirst through “zth” partial results of the list of correctly translatedwords and/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_(—)1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes ⅗ decode threshold/pillar widthratio) to produce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_(—)1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terabytes). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_(—)1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terabytes). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_(—)1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes ⅗decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage network (DSN) system 400 that includes the distributed storageand task (DST) processing unit 16 and the distributed storage and tasknetwork (DSTN) module 22 of FIG. 1. The DSTN module 22 includes aplurality of sets of DST execution units 36 (e.g., DST EX unit sets 1-3,etc.). The DST execution units 36 may be implemented at a site or aplurality of sites utilized for implementation of DST execution units 36of the DSTN module 22. One or more DST execution units 36 of one or moreDST execution unit sets may be implemented at a common site. Forexample, a first DST execution unit 36 of DST execution unit set 1 and afirst DST execution unit 36 of DST execution unit set 2 are implementedat site 1, a second DST execution unit 36 of DST execution unit set 1and a second DST execution unit 36 of DST execution unit set 2 areimplemented at site 2, etc. through an nth DST execution unit 36 of DSTexecution unit set 1 and an nth DST execution unit 36 of DST executionunit set 2 are implemented at an nth site, and a first DST executionunit 36 of DST execution unit set 3 is implemented at site n+1.

In an embodiment, the dispersed storage and task (DST) processing unit16 includes at least one module, when operable within a computingdevice, that causes the computing device to perform the following methodsteps: encode input data 402 into a plurality of slices; send theplurality of slices to a plurality of distributed storage and taskexecution units for storage, the plurality of distributed storage andtask execution units 36 that are located at a corresponding plurality ofsites; detect a storage failure corresponding to at least one of theplurality of slices corresponding to at least one of the plurality ofthe distributed storage and task execution units 36 and at least one ofthe corresponding plurality of sites; determine a foster storageapproach for selecting a foster slice to replace the slices wherestorage failed; select at least one alternative distributed storage andtask execution unit 36 in accordance with the foster storage approach;generate at least one foster slice corresponding to the at least one ofthe plurality of slices; and to send the at least one foster slice tothe at least one alternative distributed storage and task execution unit36.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions that can, when executed by one or moreprocessing modules of one or more computing devices of a dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

In an embodiment, determining the foster storage approach includesdetermining one of: a performance optimized mode, and a reliabilityoptimized mode. When the foster storage approach corresponds to theperformance optimized mode, the at least one alternative distributedstorage and task execution unit can be selected as the at least one ofcorresponding plurality of sites. When the foster storage approachcorresponds to the reliability optimized mode, the at least onealternative distributed storage and task execution unit can be selectedas at least one alternative site that is disassociated from thecorresponding plurality of sites.

In an embodiment the method described above further includes updatingslice location information corresponding to the input data when the atleast one foster slice is successfully stored in the at least onealternative distributed storage and task execution unit 36. Detecting astorage failure corresponding to at least one of the plurality of slicescan include at least one of: detecting a device failure in the at leastone of the plurality of the distributed storage and task execution units36; and detecting a communication failure to the at least one of theplurality of the distributed storage and task execution units 36. Thefoster storage approach can be determined based on at least one of: apredetermined mode selection; a vault identifier, a data typecorresponding to the input data, an estimated time of storage of theinput data, an estimated frequency of retrieval of the input data, areliability requirement of the input data, and a retrieval performancerequirement of the input data.

The further operation of the dispersed storage network (DSN) system 400,including several optional functions and features can be described inconjunction with the examples that follow.

In an example of storing data in the DSTN module 22, the DST processingunit 16 receives the data and encodes the data using a dispersed storageerror coding function to produce a set of encoded data slices 1-n. TheDST processing unit 16 selects a DST execution unit set for storage ofthe set of encoded data slices based on one or more of a DST executionunit availability indicator, a DST execution unit performance levelindicator, a data identifier, and an association of the data identifierwith a set of DST execution units. As a specific example, the DSTprocessing unit 16 selects DST execution unit set 1 for storing the setof encoded data slices 1-n when a storage location table lookupindicates that the data identifier of the data is associated with theDST execution unit set 1.

Having selected the DST execution unit set, the DST processing unit 16sends each encoded data slice of the set of encoded data slices to acorresponding DST execution unit 36 of the DST execution unit set 1. Asa specific example, the DST processing unit 16 sends encoded data slice1 to the first DST execution unit 36 of the DST execution unit set 1,the DST processing unit 16 sends encoded data slice 2 to the second DSTexecution unit 36 of the DST execution unit set 1, etc.

The DST processing unit 16 detects a storage failure of storage of anencoded data slice in an associated DST execution unit 36. The detectingmay be based on one or more of receiving an unfavorable response fromthe DST execution unit 36, not receiving a favorable storage responsefrom the DST execution unit 36 within a response timeframe, detecting anetwork failure, receiving an error message, and detecting that the DSTexecution unit 36 is inoperable. As a specific example, the DSTprocessing unit 16 detects the storage failure of storage of slice 2 tothe second DST execution unit 36 of DST execution unit 1 (represented bythe large “X”) when the favorable storage response was not receivedwithin the response timeframe.

Having detected the storage failure, the DST processing unit 16 selectsa foster storage approach based on one or more of a predetermination,the data identifier, a vault identifier, a data type indicator, anestimated time of storage, an estimated frequency of retrieval, astorage reliability requirement, and a retrieval performancerequirement. The foster storage approach includes a variety ofapproaches. A first approach includes generating and storing a fosterslice for storage in another DST execution unit 36 of the DSTN module 22to realize a performance optimization. A second approach includesstoring the foster slice in yet another DST execution unit 36 to realizea reliability optimization. For example, the DST processing unit 16selects the performance optimization foster storage approach when theestimated frequency of retrieval is higher than average frequency ofretrieval and the retrieval performance requirement is higher than anaverage retrieval performance. As another example, the DST processingunit selects the reliability optimization foster storage approach whenthe estimated time of storage is greater than an average time of storageand the storage reliability requirement is higher than an averagestorage reliability requirement.

When the foster storage approach is optimized for performance, the DSTprocessing unit 16 selects an alternate DST execution unit 36 affiliatedwith the DST execution unit 36. The alternate DST execution unitaffiliation includes at least one of co-location at a common site,co-location in a common rack, and sharing a common network accessconnection. As a specific example, the DST processing unit 16 selectsthe second DST execution unit 36 of DST execution unit set 2 implementedat site 2 in common with the second DST execution unit 36 of DSTexecution unit set 1.

When the foster storage approach is optimized for reliability, the DSTprocessing unit 16 selects the alternate DST execution unit 36 to bedisassociated with the DST execution unit 36. The disassociationprovides high failure independence and includes at least one ofimplemented at another site, included in another set of DST executionunits, powered by a different power source, utilizing a unique device,and utilizing a unique network access connection. As a specific example,the DST processing unit 16 selects the first DST execution unit 36 ofDST execution unit set 3 implemented at site n+1.

Having selected the alternate DST execution unit 36, the DST processingunit 16 issues a foster slice storage request to the alternate DSTexecution unit 36. The issuing includes one or more of generating atemporary DSN address to associate with the encoded data slice,generating the foster storage request to include the encoded data sliceand the temporary DSN address, and sending the foster slice storagerequest to the alternate DST execution unit 36. The DST processing unit16 updates slice location information (e.g., a slice location table) toassociate one or more of the encoded data slice, the temporary DSNaddress, and the alternate DST execution unit 36.

FIG. 40B is a flowchart illustrating an example of identifying alternatestorage. In particular a method is presented for use in conjunction withone or more functions and features described in conjunction with FIGS.1-39 and also FIG. 40A. The method includes step 410 where a processingmodule (e.g., of a distributed storage and task (DST) client module)sends a set of encoded data slices to a set of storage units for storagetherein. The sending includes issuing a set of write slice requests tothe set of storage units that includes the set of encoded data slices.The method continues at step 412 where the processing module detects astorage failure of an encoded data slice to an unavailable storage unit.The detecting includes at least one of determining that a favorablewrite slice responses that the received from the unavailable storageunit within a response timeframe, receiving an unfavorable write sliceresponse from the unavailable storage unit, and receiving an errormessage.

The method continues at step 414 where the processing module identifiesa foster storage approach. The identifying may be based on one or moreof a requesting entity identifier, a data type, a data identifier, avault identifier, an amount of estimated storage required, an estimatedretrieval frequency, a reliability requirement, and a retrievalperformance requirement. The method branches to step 416 where theprocessing module identifies the alternate storage unit disassociatedwith the unavailable storage unit when the foster storage approach isoptimized for reliability. The method continues to step 415 when thefoster storage approach is optimized for performance. The methodcontinues at step 415 when the foster storage approach is optimized forperformance, where the processing module identifies an alternate storageunit associated with the unavailable storage unit. For example, theprocessing module selects the alternate storage unit based on a highdegree of affinity with the unavailable storage unit. For instance, theprocessing module selects the alternate storage unit for at least one ofa similar performance level, implemented at a common site, implementedin a common rack, a common model, and a common software version. Themethod branches to step 418 where the processing module issues a fosterslice storage request.

When the foster storage approach is optimized for reliability, themethod continues at step 416 where the processing module identifies thealternate storage unit disassociated with the unavailable storage unit.The identifying includes selecting the alternate storage unit based on alow level of affinity with the unavailable storage unit. For example,implemented at a different site, a different model, utilizing adifferent power source, utilizing a different communication path under adifferent management domain, and utilizing a different software version.

The method continues at step 418 where the processing module issues afoster slice storage request to the identified alternate storage unitthat includes the encoded data slice associated with the storagefailure. The issuing includes generating the foster slice storagerequest to include one or more of the encoded data slice, a slice name,a temporary slice name, an estimated time of storage, a temporary accesscontrol list, and temporary access credentials. The method continues atstep 420 where the processing module updates slice location information.For example, the processing module updates a dispersed storage network(DSN) address-to-slice location table to associate the slice name to theidentified alternate storage unit and to disassociate the unavailablestorage unit and the slice name.

FIGS. 41A and 41B are schematic block diagrams of other embodiments of adispersed storage network (DSN) system 500 that includes the distributedstorage and task (DST) processing unit 16 and the distributed storageand task network (DSTN) module 22 of FIG. 1. The DSTN module 22 includesa primary DST execution unit set 504 and a secondary DST execution unitset 506. Each of the primary and secondary DST execution unit setsincludes a set of DST execution units 36 of FIG. 1. The DST executionunits 36 may be implemented at a site of a plurality of sites utilizedfor implementation of DST execution units 36 of the DSTN module 22. Atleast one DST execution unit 36 of at least one of the primary andsecondary DST execution unit sets is implemented at a unique site. Forexample, as illustrated in FIG. 41A, all DST execution units 36 of thesecondary DST execution unit set are implemented at site n+1 and all DSTexecution units 36 of the primary DST execution unit set are implementedat sites 1−n. As another example, as illustrated in FIG. 41B, one DSTexecution unit 36 of the secondary DST execution unit set 503 isimplemented at site n+1 and all remaining DST execution units 36 of thesecondary DST execution unit set and all DST execution units 36 of theprimary DST execution unit set 501 are implemented at sites 1−n.

In an embodiment, the dispersed storage and task (DST) processing unit16 includes at least one module, when operable within a computingdevice, that causes the computing device to perform the following methodsteps: encoding input data 502 into a plurality of slices; sending theplurality of slices to a first plurality of distributed storage and taskexecution units 36 for storage, the first plurality of distributedstorage and task execution units 36 being located at a correspondingfirst plurality of sites; receiving write slice data from the firstplurality of distributed storage and task execution units 36;determining when replication is to be applied to the plurality ofslices. When replication is to be applied to the plurality of slices:selecting a second plurality of distributed storage and task executionunits 36; generating a plurality of replicated slices corresponding tothe plurality of slices; and sending the plurality of replicated slicesto the second plurality of distributed storage and task execution units36.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions that can, when executed by one or moreprocessing modules of one or more computing devices of a dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

In an embodiment, determining when replication is to be applied to theplurality of slices is based on at least one of: analyzing the writeslice responses, a requester identification, a data identification, adata type indication, a vault identification, and a replication modepredetermination. Determining when replication is to be applied to theplurality of slices can include analyzing the write slice responses todetermine when at least one storage error occurred. Determining whenreplication is to be applied to the plurality of slices can includeanalyzing the write slice responses to determine a number of storageerrors and to determine when the number of storage errors comparesunfavorably to a replication threshold. Determining when replication isto be applied to the plurality of slices can include analyzing the writeslice responses to determine a number of favorable write slice responsesand to determine when the number of favorable write slice responsescompares unfavorably to a replication threshold. The second plurality ofdistributed storage and task execution units 36 can be selected tocorrespond to at least one site that is disassociated with the firstplurality of sites. The second plurality of distributed storage and taskexecution units 36 can be selected based on at least one of: apredetermined selection, a column availability, a reliability metric, astorage requirement associated with the plurality of slices, and one ormore sites associated with the second plurality of distributed storageand task execution units 36.

The further operation of the dispersed storage network (DSN) system 500,including several optional functions and features can be described inconjunction with the examples that follow.

In an example of storing data in the DSTN module 22, the DST processingunit 16 includes the data using a dispersed storage error codingfunction to produce a set of encoded data slices and sends the set ofencoded data slices to the primary DST execution unit set for storagetherein. The DST processing unit 16 receives write slice responses fromthe primary DST execution unit set with regards to status of writing(e.g., favorable, unfavorable). The DST processing unit 16 determineswhether to replicate the set of encoded data slices. The determining maybe based on one or more of a requesting entity identifier, a dataidentifier, a data type indicator, a vault identifier, apredetermination, receiving an error message, and the write sliceresponses. For example, the DST processing unit 16 determines toreplicate the set of encoded data slices when one storage error isdetected. As another example, the DST processing unit 16 determines toreplicate the set of encoded data slices when not receiving at least awrite threshold number of favorable write slice responses from the setof storage units within a response timeframe.

When replicating, the DST processing unit 16 selects one or morealternate DST execution units 36 to form the secondary DST executionunit set, where at least one alternate DST execution unit 36 isimplemented at a unique site with regards to implementation of DSTexecution units 36 of the primary DST execution unit set. The selectingmay be based on one or more of a predetermination, current availability,a reliability level, a storage requirement, and a reserved storage unitindicator. For example, the DST processing unit 16 selects a set of DSTexecution units 36 based on a list of DST execution units 36 associatedwith a reserved set of DST execution units 36.

Having selected the secondary DST execution unit set, the DST processingunit 16 sends the set of encoded data slices as a replicated set ofencoded data slices to the secondary DST execution unit set for storagetherein. The sending may include sending a replicated slice to a DSTexecution unit 36 implemented at a site that is not common to a sitewhere an associated encoded data slice is stored within a DST executionunit 36 of the primary DST execution unit set. For example, the DSTprocessing unit 16 sends a replicated slice 2 to a second DST executionunit 36 of the secondary DST execution unit set that is implemented atsite n+1 as illustrated in FIG. 41A. As another example, the DSTprocessing unit 16 sends the replicated slice 2 to a first DST executionunit 36 of the secondary DST execution unit set that is implemented atsite 1 as illustrated in FIG. 41B (e.g., since slice 2 is stored in asecond DST execution unit 36 of the primary DST execution unit set atsite 2).

Having sent the set of replicated encoded data slices to the secondaryDST execution unit set, the DST processing unit 16 updates slicelocation information to enable subsequent data recovery from retrievinga set of encoded data slices from one or more of the primary andsecondary DST execution unit sets. The updating includes associatingslice names of the encoded data slices with identifiers of associatedDST execution units 36.

FIG. 41C is a flowchart illustrating an example of replicating encodeddata slices, which includes similar steps to FIG. 40B. In particular amethod is presented for use in conjunction with one or more functionsand features described in conjunction with FIGS. 1-39 and also FIGS.40A, 40B, 41A and 41B. The method includes step 510 where a processingmodule (e.g., of a distributed storage and task (DST) client module)sends a set of encoded data slices to a primary set of storage units anda set of sites for storage. The sending includes issuing a set of writeslice requests to the primary set of storage units that includes the setof encoded data slices. The method continues at step 512 where theprocessing module determines a level of storage access. The determiningincludes interpreting write slice responses from the primary set ofstorage units. The method continues at step 514 where the processingmodule determines whether to replicate the set of encoded data slices.The determining may be based on one or more of a requester identifier, adata identifier, a data type indicator, a vault identifier, apredetermination, a level of storage access, and a received errormessage. For example, the processing module determines to replicate theset of encoded data slices when the level of storage access indicatesthat less than a write threshold number of favorable write sliceresponses has been received from the primary set of storage units.

When replicating, the method continues at step 516 where the processingmodule selects one or more alternate storage units where at least one ofthe one or more alternate storage units is associated with another site(e.g., different than the set of sites associated with the primary setof storage units. The selecting includes at least one of utilizing analternate storage unit from a list of reserved storage units andselecting one or more reserved storage units based on one or more ofalternate storage unit availability and reliability to produce theselected one or more alternate storage units. The method continues atstep 518 where the processing module sends a replicated set of slices tothe one or more alternate storage units for storage. The sendingincludes one or more of generating an alternate set of slice names,generating replicated write slice requests that includes the set ofencoded data slices and the alternate set of slice names, and outputtingthe replicated write slice requests to the one or more alternate storageunits. The method continues at step 520, similar to step 420 of FIG.40B, where the processing module updates slice location information.

FIG. 42A is a schematic block diagram of another embodiment of adistributed computing system 600 that includes the distributed storageand task (DST) client module 34 and the distributed storage and tasknetwork (DSTN) module 22 of FIG. 1. The DST client module 34 includesthe outbound DST processing 80 and the inbound DST processing 82 of FIG.3. The DSTN module 22 includes a DST execution unit set 604 thatincludes a set of DST execution units 36 of FIG. 1. The system functionsto process a task 94 by coordinating execution of associated partialtasks by the set of DST execution units 36 to produce a result 104.

In an embodiment, the dispersed storage and task (DST) client module 34includes at least one module, when operable within a computing device,that causes the computing device to perform the following method steps:receiving a task 94 for execution by a plurality of distributed storageand task execution units 36; determining a priority level for the task94; generating a plurality of coordinated partial task requests 602 tothe plurality of distributed storage and task execution units 36,wherein the plurality coordinated partial task requests 602 indicate aplurality of coordinated partial tasks and the priority level; receivinga plurality of partial task results 102 in response to performance ofthe plurality of coordinated partial tasks by the plurality ofdistributed storage and task execution units; and generating a taskresult 104 for the task 94 based on the plurality of partial taskresults 102.

The method described above in conjunction with the DST client module 34can alternatively be performed by other modules of a dispersed storagenetwork, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions that can, when executed by one or moreprocessing modules of one or more computing devices of a dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

In an embodiment, the plurality of distributed storage and taskexecution units 36 determine when to commence the plurality ofcoordinated partial tasks based on at least one of: at least oneresource availability, and the priority level. At least one of theplurality of distributed storage and task execution units 36 cancommunicate at least one of the plurality of partial task results 102with at least one other of the plurality of distributed storage and taskexecution units 36. At least one other of the plurality of distributedstorage and task execution units 36 generates at least one other of theplurality of partial task results 102 based on the at least one of theplurality of partial task results 102 received from the at least one ofthe plurality of distributed storage and task execution units 36. Thetask 94 can include one of: aborted transaction clean up from at leastone prior aborted task, a data migration, expired data clean upcorresponding to stored data that has expired, a snapshot clean up, anindex health check, a segment health check, a scan for missing slices,and a system maintenance task. At least one of the plurality ofdistributed storage and task execution units 36 can communicateprocessing resource availability information with at least one other ofthe plurality of distributed storage and task execution units 36;wherein the processing resource availability information includes atleast one of: a current processing utilization, an estimated processingutilization, indication of at least one pending one of the plurality ofcoordinated partial tasks, a completion forecast for the at least onepending one of the plurality of coordinated partial tasks, and acommencement forecast for at least one non-pending one of the pluralityof coordinated partial tasks. At least one of the plurality ofdistributed storage and task execution units 36 can communicatecoordination information with at least one other of the plurality ofdistributed storage and task execution units 36, wherein thecoordination information relates to execution of another plurality ofcoordinated partial tasks.

The further operation of the dispersed storage network (DSN) system 600,including several optional functions and features can be described inconjunction with the examples that follow.

In an example of coordinating execution of the associated partial tasks,the outbound DST processing 80 receives the task 94 and identifies thetask 94 to require co-execution of partial tasks by the set of DSTexecution units. The identifying includes at least one of receiving arequest, performing a lookup, initiating a query, receiving a response,and identifying a time criticality component to the partial tasks of thetask 94. The task 94 includes at least one of orphan slice detection,aborted transaction cleanup, data migration, expiration policy cleanup,deleting slices, snapshot cleanup, index health check, segment healthcheck, scanning for missing slices, re-encrypting slices, and othersimilar maintenance tasks.

The outbound DST processing 80 determines a priority level for the task94 based on one or more of other currently pending tasks, other expectedfuture tasks, an estimated reliability impact, an estimated performanceimpact, the requested priority level, and a predetermined prioritylevel. For example, the outbound DST processing 80 determines thepriority level for the task 94 to be a higher than average prioritylevel when the estimated performance impact indicates that immediateco-execution of associated partial tasks is required.

Having determined the priority level for the task 94, the outbound DSTprocessing 80 generates a set of coordinated partial tasks based on thetask 94 and the priority level such that co-execution of the coordinatedpartial tasks by the set of DST execution units 36 facilitatesgeneration of the result 104. The outbound DST processing 80 sends theset of coordinated partial tasks and the priority level to the DSTexecution unit set for coordinated execution. The set of DST executionunits determines when to commence execution of the set of coordinatedpartial tasks based on shared processing resource availabilityinformation. The shared processing resource availability informationincludes one or more of current processing utilization levels, estimatedprocessing utilization levels, a list of pending partial tasks, prioritylevels of pending partial tasks, and a forecast for when anothercoordinated partial task can be co-executed by the set of DST executionunits 36. For example, the set of DST execution units determines tocommence execution of the set of coordinated partial tasks in fiveseconds when other pending tasks are forecasted to have completed andthere are no other higher priority pending tasks.

Having determined went to commence the execution of the set ofcoordinated partial tasks, the set of DST execution units executes theset of coordinated partial tasks. The execution includes one or more ofgenerating partial results 102, sharing the partial results 102 withother DST execution units 36, and sending the partial results 102 to theinbound DST processing 82. For example, a DST execution unit 36 executesan assigned coordinated partial task to generate a interim partialresult 102. Next, the DST execution unit 36 sends the interim partialresult 102 to another DST execution unit 36. The other DST executionunit 36 executes its own assigned coordinated partial task using theinterim partial result 102 to generate another partial result 102. Theinbound DST processing 82 receives partial results 102 from the set ofDST execution units 36 and aggregates the partial results 102 to producethe result 104.

FIG. 42B is a flowchart illustrating an example of coordinating taskexecution. In particular a method is presented for use in conjunctionwith one or more functions and features described in conjunction withFIGS. 1-39 and also FIGS. 40A, 40B, 41A, 41B, 41C and 42A.

The method includes step 610 where a processing module (e.g., of adistributed storage and task (DST) client module) identifies a taskrequiring co-execution by a set of DST execution units. The identifyingmay include one or more of receiving the task, comparing the task to acoordination list, generating a set of partial tasks, and identifying acommonality of the set of partial tasks (e.g., a set of partial tasksassociated with a common set of slices stored in the set of DSTexecution units). The method continues at step 612 where the processingmodule determines a priority level for the task. The determining may bebased on one or more of other currently pending tasks, other expectedfuture tasks, an estimated reliability impact, an estimated performanceimpact, a requested priority level, and a predetermined priority level.

The method continues at step 614 where the processing module issues aset of coordinated partial task requests to the set of DST executionunits. The issuing includes generating the set of coordinated partialtasks based on the task, generating each request to include acoordinated partial task corresponding to the task and the prioritylevel, and sending the set of coordinated partial tasks to the set ofDST execution units. The method continues at step 616 where the set ofDST execution units share processing resource availability information.For example, from time to time, each DST execution unit generatesassociated processing resource availability information and outputs theassociated processing resource availability information to other DSTexecution units. Alternatively, timing of the outputting may be based onone or more of a schedule, a request, and a corrugated partial task.

The method continues at step 618 where the set of DST execution unitsdetermines an execution schedule for the set of coordinated partialtasks. The determining may be based on the processing resourceavailability information and the set of coordinated partial tasks. Forexample, the DST execution units determine to execute the set ofcoordinated partial tasks when other higher priority tasks are complete.The method continues at step 620 where the set of DST execution unitsexecutes the set of coordinated partial task requests in accordance withthe execution schedule. For example, each DST execution unit executesits portion of the task by executing a corresponding coordinated partialtask to produce a partial result. The execution of the correspondingcoordinated partial task may include receiving a partial result fromanother DST execution unit and utilizing the received partial result toexecute the corresponding coordinated partial task. Each DST executionunit sends a resulting partial result to the processing module.

The method continues at step 624 where the processing module receivesthe partial results from the set of DST execution units. The methodcontinues at step 626 where the processing module issues a result basedon a partial results. The issuing includes generating the result basedon the set of partial results. For example, the processing module issuesa data segment integrity result based on receiving a set of partialresults associated with integrity of a set of encoded data slices of thedata segment.

FIG. 43A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system 700 that includes at least twodistributed storage and task (DST) client modules and a distributedstorage and task network (DSTN) module 22. The DSTN module 22 includes aDST execution unit set 702. Each DST client module includes the outboundDST processing 80 and the inbound DST processing 82 of FIG. 3. Data isencoded using a dispersed storage error coding function in accordancewith dispersal parameters that includes a decode threshold number toproduce sets of encoded data slices for storage in the DST executionunit set. The DST execution unit set includes a set of DST executionunits 36, where at least a decode threshold number of DST executionunits 36 are implemented at a first site and a decode threshold numberof other DST execution units are implemented at a second site.Accordingly, the set of DST execution units includes at least twice thenumber of the decode threshold of DST execution units.

Each DST client module is associated with one site based on an accessperformance affinity (e.g., lowest access delays compared to othersites) with DST execution units 36 implemented at the one site. Forexample, a first DST client module is more geographically proximal tothe first site than the second site and a second DST client module ismore geographically proximal to the second site than the first site. Assuch, access performance between the first DST client module and DSTexecution units implemented at the first site is more favorable thanaccess performance between the first DST client module and DST executionunits implemented at the second site. Likewise, access performancebetween the second DST client module and the DST execution unitsimplemented at the second site is more favorable than access performancebetween the second DST client module and DST execution units implementedat the first site.

In an embodiment, the dispersed storage and task (DST) processing unit16 includes at least one module, when operable within a computingdevice, that causes the computing device to perform the following methodsteps: identifying a plurality of DST client modules (1 and 2)affiliated with data for storage in a DST network; identifying acorresponding subset of a plurality of DST execution units 36 for eachof the plurality of DST client modules; encoding the data into aplurality of slices based on at least one dispersal parameter, thenumber of the plurality of slices corresponding to a number of theplurality of DST execution units 36 included in a superset formed fromthe union of each subset of a plurality of DST execution units 36corresponding to each of the plurality of DST client modules, in thisfashion a slice is generated for storage in each of a plurality of DSTexecution units 36 that are included in each DST client module subset;and sending the plurality of slices for storage in the superset of theplurality of DST execution units 36, formed from the union of eachsubset of the plurality of DST execution units 36.

The method described above in conjunction with the DST processing unit16 can alternatively be performed by other modules of a dispersedstorage network, of a dispersed storage and tracking network or by otherdevices. In addition, at least one memory section that storesoperational instructions that can, when executed by one or moreprocessing modules of one or more computing devices of a dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

In an embodiment, identifying the corresponding subset of the pluralityof DST execution units for each of the plurality of DST client modulesincludes identifying at least a number of the plurality of DST executionunits 36 corresponding to a decode threshold. Identifying thecorresponding subset of the plurality of DST execution units 36 for eachof the plurality of DST client modules can include identifying ones ofthe plurality of DST execution units 36 having a favorable accessperformance level for the corresponding one of the plurality of DSTclient modules. The at least one dispersal parameter can include atleast one of: a number of the plurality of DST execution units 36corresponding to a decode threshold, a pillar width number that isgreater than a multiple (such as two or greater) of the number of theplurality of DST execution units corresponding to a decode threshold.The method can further include attempting retrieval, by one of theplurality of DST client modules, of a first subset of the plurality ofslices from the subset of a plurality of DST execution units 36corresponding to the one of the plurality of DST client modules;determining when the attempted retrieval yields less than a decodethreshold number of the plurality of slices; and when the attemptedretrieval yields less than the decode threshold number of the pluralityof slices, attempting further retrieval from at least one other of theplurality of DST execution units included in the superset formed fromthe union of each subset of a plurality of DST execution units. Thesuperset formed from the union of each subset of a plurality of DSTexecution units can include at least one DST execution unit 36 at aplurality of different sites.

The further operation of the dispersed storage network (DSN) system 700,including several optional functions and features can be described inconjunction with the examples that follow.

In an example of storing data, the first DST client module identifies atleast one other DST client module affiliated (e.g., expected tosubsequently retrieve the data) with data for storage in the DSTN module22. For instance, the first DST client module identifies the second DSTclient module. For each of the two or more DST client modules, the firstDST client module identifies a subset of DST execution units 36 thatincludes at least a common decode threshold number of DST execution unit36, and where the subset of DST execution units 36 is associated withthe access performance affinity (e.g., a favorable access performancelevel) for the affiliated DST client module. The identifying includes atleast one of performing a test, initiating a query, performing a lookup,accessing a historical record, and receiving an error message. Forexample, the first DST client module identifies the DST execution units36 implemented at site 1 to be affiliated with the first DST clientmodule and identifies the DST execution units 36 implemented at site 2to be affiliated with the second DST client module based on aperformance test.

The first DST client module (e.g., the outbound DST processing 80)encodes the data using the dispersed storage error coding function andthe dispersal parameters to produce a set of encoded data slices, wherethe set of encoded data slices includes a unique subset of at least adecode threshold number of encoded data slices for each DST clientmodule. Accordingly, the dispersal parameters includes a pillar widthnumber that is greater than or equal to a multiple number of commondecode threshold numbers. For the example, the pillar width is greaterthan or equal to 10 when the decode threshold is five and there are twoDST client modules. As another example, the pillar width is greater thanor equal to 15 when the decode threshold is five and there are three DSTclient modules. Having encoded the data to produce the set of encodeddata slices, the first DST client module sends the set of encoded dataslices to the set of DST execution units 36. For instance, a firstsubset of slices is sent to DST execution units 36 of site 1 and asecond subset of slices is sent to DST execution units 36 of site 2.

The data may be retrieved by either of the first or second DST clientmodules. In an example of retrieving the data by the first DST clientmodule, the inbound DST processing 82 of the first DST client moduleidentifies the DST execution unit set associated with the data (e.g., adirectory lookup, a dispersed hierarchical index search). Next, thefirst DST client module identifies the subset of DST execution units 36associated with the first DST client module based on the accessperformance affinity. For instance, the first DST client moduleidentifies the DST execution units 36 implemented at site 1. The firstDST client module initiates retrieval of a decode threshold number ofencoded data slices from the identified subset of DST execution units 36at site 1. When the decode threshold number of encoded data slices arenot available from the identified subset of DST execution units 36, thefirst DST client module retrieves one or more further encoded dataslices from another subset of DST execution units 36. For example, thefirst DST client module retrieves the one or more encoded data slicesfrom DST execution units 36 implemented at site 2. When the decodethreshold number of encoded data slices are received, the first DSTclient module decodes the received encoded data slices using thedispersed storage error coding function to reproduce the data.

FIG. 43B is a flowchart illustrating an example of accessing data. Inparticular a method is presented for use in conjunction with one or morefunctions and features described in conjunction with FIGS. 1-39 and alsoFIGS. 40A, 40B, 41A, 41B, 41C, 42A, 42B and 43A.

The method includes step 710 to store data where a processing module(e.g., of a distributed storage and task (DST) client module) identifiestwo or more DST client modules affiliated with data for storage in adispersed storage network (DSN). For each DST client module, theprocessing module identifies a subset of storage units based on anaccess performance affinity as shown in step 712. Two or more DST clientmodules may have an access performance affinity with a common subset ofstorage units.

The method continues at step 714 where the processing module encodesdata to produce a set of encoded data slices that includes at least acommon decode threshold number of encoded data slices for each subset ofstorage units. For each subset of storage units, the method continues atstep 716 where the processing module stores a corresponding at least thecommon decode threshold number of encoded data slices. For example, theprocessing module stores each unique combination of a decode thresholdnumber of encoded data slices in each subset of storage units.

The method continues at step 718 to retrieve data where the processingmodule identifies the set of storage units associated with the data. Themethod continues at step 720 where the processing module identifies asubset of storage units of the set of storage units based on the accessperformance affinity. The method continues at step 722 where theprocessing module initiates retrieval of a decode threshold number ofencoded data slices from the subset of storage units. For example, theprocessing module issues a decode threshold number of read slicerequests and receives encoded data slices. When the decode thresholdnumber of encoded data slices are not available from the subset ofstorage units, the method continues at step 724 where the processingmodule retrieves one or more further encoded data slices from anothersubset of storage units. The retrieving includes identifying the othersubset of storage units based on a next best access performance affinity(e.g., next best compared to the access performance affinityrelationship between the DST client module and the subset of storageunits). When receiving the decode threshold number of encoded dataslices, the method continues at step 726 where the processing moduledecodes the decode threshold number of received encoded data slices toreproduce the data.

FIG. 44A is a schematic block diagram of another embodiment of adistributed computing system 800 that includes a distributed storage andtask network (DSTN) managing unit 18, a DST client module 34, and a DSTexecution unit set 802. The DST execution unit set includes one or morephysical DST execution units 1-p. Each physical DST execution unitincludes one or more virtual DST execution units of a set of virtual DSTexecution units 1-n. A virtual DST execution unit includes a logicalimplementation of functions of the DST execution unit 36 of FIG. 1. Eachvirtual DST execution unit is associated with a DSN address rangeassignment with regards to accessing encoded data slices associated withslice names that fall within the DSN address range assignment.

The DSTN managing unit 18 determines the DSN address ranges inaccordance with storage capacity and processing capability of thephysical DST execution units and forecasted storage loading and taskprocessing loading. For example, the DSTN managing unit 18 assignsvirtual DST execution units 1-3 to physical DST execution unit 1 whenthe storage capacity of the physical DST execution unit is greater thanthe forecasted storage loading for the three virtual DST executionunits. As another example, the DSTN managing unit 18 assigns virtual DSTexecution units 4-5 to physical DST execution unit 2 when the processingcapability of the physical DST execution unit 2 is greater than theforecasted task processing loading for the two virtual DST executionunits.

The DSTN managing unit 18 issues DSN address range assignments to thephysical DST execution units to establish the DSN address rangeassignment association with each virtual DST execution unit of eachphysical DST execution unit. For example, at a first timeframe t0, theDSTN managing unit 18 issues the DSN address range assignments to assignthree pillars of a common DSN address range to virtual DST executionunits 1-3 of physical DST execution unit 1. For instance, a pillar 1slices of the common DSN address range are assigned to virtual DSTexecution unit 1, pillar 2 slices of the common DSN address range areassigned to virtual DST execution unit 2, and pillar 3 slices of thecommon DSN address range are assigned to virtual DST execution unit 3.As another example, at the first timeframe t0, the DSTN managing unit 18issues additional DSN address range assignments to assign to morepillars of the common DSN address range to virtual DST execution units1-2 of physical DST execution unit 2.

The DST client module 34 may access the DST execution unit set inaccordance with the DSN address range assignments to access encoded dataslices stored within a set of virtual DST execution units. For example,the DST client module 34 sends an access request for pillars 1-3 of thecommon DSN address range to the physical DST execution 1 and sendsremaining access requests for pillars 4-5 to physical DST execution unit2 to access a set of encoded data slices associated with virtual DSTexecution units 1-3 within the physical DST execution unit 1 and virtualDST execution units 4-5 associated with physical DST execution unit 2.

In an example of operation, the DSTN managing unit 18 receives a requestto commission a set of storage units for a DSN address range. The DSTNmanaging unit 18 identifies one or more physical storage units for thecommissioning based on one or more of a manager input, storage unitavailability information, a request, and a query response. The DSTNmanaging unit 18 determines capability level information for each of theone or more physical storage units. The capability level informationincludes one or more of available storage capacity, available taskprocessing capability, current utilization levels, and forecastedutilization levels. The determining may be based on one or more ofregistry information, monitoring activity, performing a test, initiatinga query, and receiving information.

The DSTN managing unit 18 determines mapping information (e.g., storageDSN address range, processing DSN address range) of a set of virtualstorage units to the one or more physical storage units in accordancewith the capability level information. The DSTN managing unit 18 issuesDSN address range assignments to the one or more physical storage unitsthat includes the mapping information.

When identifying an additional physical storage unit, the DSTN managingunit 18 determines updated mapping information based on updatedcapability level information. The DSTN managing unit 18 issues updatedDSN address range assignments to update the one or more physical storageunits that includes the updated mapping information. An example ofupdating assignment of virtual storage units to physical storage unitsis discussed in greater detail with reference to FIG. 44B.

FIG. 44B is a diagram illustrating an example of a migration of virtualstorage units within physical storage units that includes mappinginformation of a set of virtual storage units (VU 1-5) to one or morephysical storage units (PU 1-5). At a first timeframe t0, there are twoavailable physical storage units to provide required storage capacityand task processing capacity. An initial mapping includes assignment ofvirtual storage units 1-3 to physical storage unit 1 and assignment ofvirtual storage units 4-5 physical storage unit 2.

At a second timeframe t1, there is an additional physical storage unitavailable to provide a total of three physical storage units. A nextmapping includes assignment of virtual storage units 1-2 to physicalstorage unit 1, virtual storage unit 3 to physical storage unit 3 (e.g.,virtual storage unit 3 slices are migrated to storage unit 3), andvirtual storage units 4-5 remain mapped to physical storage unit 2(e.g., not requiring slice migration).

At a third timeframe t2, there are two more additional physical storageunits available to provide a total of five physical storage units. Anext mapping includes assignment of one virtual storage unit to onephysical storage unit. As a result, slices associated with virtualstorage unit 2 are moved from physical storage unit 1 to physicalstorage unit 5, slices associated with virtual storage unit 4 are movedfrom virtual storage unit 2 to physical storage unit 4.

FIG. 44C is a flowchart illustrating an example of commissioning storageunits. The method includes step 810 where a processing module (e.g., ofa distributed storage and task network (DSTN) managing unit) receives arequest to commission a set of storage units for a dispersed storagenetwork (DSN) address range. The request includes one or more of the DSNaddress range, dispersal parameters (e.g., a pillar width number),identities of candidate physical storage units, forecasted storageloading levels, and forecasted task processing loading levels.

The method continues at step 812 where the processing module identifiesone or more physical storage units to associate with the DSN addressrange. The method continues at step 814 where, for each physical storageunit, the processing module determines capability level information. Themethod continues at step 816 where the processing module determinesmapping information for mapping the DSN address range to the one or morephysical storage units in accordance with the capability levelinformation. The determining includes identifying a pillar width numberof DSN address sub-ranges (e.g., by pillar number) of the DSN addressrange. For each physical storage unit, the processing module allocates astorage DSN address sub-range and a processing DSN address sub-range ofthe DSN address range based on the capability level information of theone or more physical storage units. For each storage DSN addresssub-range, the processing module allocates one or more DSN addresssub-ranges. For each processing DSN address sub-range, the processingmodule allocates one or more of the DSN address sub-ranges.

The method continues at step 818 where the processing module issues DSNaddress range assignments for the one or more physical storage unitsthat includes the mapping information. When identifying an additionalphysical storage unit, the method continues at step 820 where theprocessing module determines updated mapping information based onupdated capability level information. For example, the processing moduledetects the additional physical storage unit based on receiving amessage. As another example, the processing module initiates updatingcapability level information (e.g., capability levels may have changedfor one or more of the storage units).

The method continues at step 822 where the processing module issuesupdated DSN address range assignments to update one or more physicalstorage units that includes the updated mapping information. Forexample, the processing module sends the updated DSN address rangeassignments to each physical storage unit. As another example, theprocessing module sends the updated DSN address range assignments tophysical storage units associated with changes between the mappinginformation and the updated mapping information. Alternatively, or inaddition to, the processing module facilitates migrating the encodeddata slices from a first physical storage unit to a second physicalstorage unit when a virtual storage unit has been reassigned from thefirst physical storage unit to the second physical storage unit as aresult of the updated mapping information.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage network (DSN) system 900 that includes the distributedstorage and task (DST) integrity processing unit 20, the DST clientmodule 34, the network 24, and the DST execution unit 36 of FIG. 1.Alternatively, the DST integrity processing unit 20 may be implementedas the DST execution unit 36. The DST client module 34 may beimplemented as the user device 12 or the DST processing unit 16 of FIG.1.

The DST integrity processing unit 20 issues rebuilding access requestsvia the network 24 to the DST execution unit 36 to facilitate rebuildingthe one or more encoded data slices associated with a slice error. Therebuilding access requests include one or more of a list range request,a list digest of a range request, a read slice request, a write rebuiltslice request. Substantially simultaneously, the DST client module 34issues slice access requests via the network 24 to the DST executionunit 36 with regards to accessing encoded data slices stored in the DSTexecution unit 36. The slice access requests include at least one of aread request, a write request, a delete request, and a list request. Arate of the rebuilding access requests may be associated with acontrolled rate (e.g., by the DST integrity processing unit 20) ofrebuilding encoded data slices based on a rate of detecting the sliceerrors. A rate of the slice access requests may be associated with arate of accessing by a plurality of DSN users.

The DST execution unit 36 may be associated with an overall access rateto accommodate both the rebuilding access requests and the slice accessrequests. As such, the DST execution unit may accommodate morerebuilding access requests when there are fewer slice access requests ormay accommodate more slice access requests when there are fewerrebuilding access requests. Accordingly, when the DST integrityprocessing unit 20 establishes the rate for the rebuilding accessrequests, a resulting rate of slice access requests may be realized(e.g., roughly as a difference between the overall access rate minus theestablished rate for the rebuilding access requests).

The DST integrity processing unit 20 determines the rate for therebuilding access requests to achieve the desired rebuilding accessrequest rate and a resulting acceptable rate of the slice accessrequests. As an example, the DST integrity processing unit 20 detectsresulting slice access performance rates for a corresponding selectedrebuilding access performance rates to produce scoring information. Whenadjusting the rate for the rebuilding access request, the DST integrityprocessing unit selects the rate for the rebuilding access requestsbased on a desired rate of slice access requests in accordance with thescoring information. From time to time, the DST integrity processingunit 20 updates the scoring information based on observed rates of sliceaccess requests for corresponding selected rates for the rebuildingaccess requests. Such scoring information is discussed in greater detailwith reference to FIG. 45B.

FIG. 45B is a timing diagram illustrating an example 905 of accessperformance that includes a graphical indication of resulting sliceaccess performance levels (e.g. megabytes per second) for selectedrebuilding access performance levels (e.g., megabytes per second) for aseries of time intervals 1-8, and a resulting set of scores for the setof time intervals. The score may be generated based on a function ofslice access performance rate and slice rebuilding access rate. Forexample, the score may be calculated in accordance with a scoringformula: score=((3*rebuild rate)+ access rate)̂2.

For a given selected rebuilding rate, an associated score may besubsequently updated in accordance with a learning rate function when anupdated corresponding slice access rate is measured for the givenselected rebuilding rate. For example, the associated score may besubsequently updated in accordance with a learning rate function formulaof: updated score=(old score)*(1-learning rate)+(new score*learningrate). For instance, updated score=81=80*(1−0.1)+(90*0.1), when thelearning rate is 10%, the old score is 80, and the new score is 90.

FIG. 45C is a flowchart illustrating an example of prioritizing accessrates. The method includes step 910 where a processing module (e.g., ofa distributed storage and task (DST) integrity processing unit) monitorsa slice access rate to produce an observed slice access rate for anassociated rebuilding rate of a set of rebuilding rates. The monitoringincludes at least one of performing a test, initiating a query, andreceiving access rate information.

The method continues at step 912 where the processing module applies alearning function to the observed slice access rate based on a previousobserved slice access rate associated with the rebuilding rate toproduce an updated previous observed slice access rate of a set ofprevious observed slice access rates, where the set of previous observedslice access rates corresponds to the set of rebuilding rates. Themethod continues at step 914 where the processing module updates a scoreassociated with the updated previous observed slice access rate and therebuilding rate.

In an example of updating a rebuilding rate, the method continues atstep 916 where the processing module determines to update the rebuildingrate for a storage unit. The determining may be based on one or more ofdetecting an end of a time interval, receiving a request, receiving anerror message, and detecting an unfavorable slice access rate. Themethod continues at step 918 where the processing module determinesslice access demand rate and rebuilding access demand rate. Thedetermining may be based on one or more of interpreting a queue,receiving a request, and accessing a historical record.

The method continues at step 920 where the processing module identifiesa prioritization scheme of one of a slice access priority scheme, acompromise scheme, and a rebuilding priory scheme. The identifying maybe based on one or more of a predetermination, detecting that a demandrate is much greater than a demand threshold level, and receiving arequest. For example, the processing module selects the slice accesspriority scheme when the slice access demand rate is much greater thanthe rebuilding access demand rate. As another example, the processingmodule selects the rebuilding priory scheme when the rebuilding accessdemand rate is much greater than the slice access demand rate. As yetanother example, the processing module selects the compromise schemewhen the slice access demand rate and the rebuilding access demand rateare similar.

When the processing module selects the compromise prioritization scheme,the method continues at step 922 where the processing module selects arebuilding rate of the set of rebuilding rates that is less than therebuilding access demand rate and maximizes a score associated with anexpected slice access rate. The selecting may be based on one or more ofaccessing a table, accessing a record, and calculating the rebuildingrate. When the processing module selects the slice access priorityscheme, the method continues at step 924 where the processing moduleselects the rebuilding rate of the set of rebuilding rates such that anestimated slice access rate is greater than the slice access demandrate. For example, the processing module selects the rebuilding ratefrom the scoring information such that the rebuilding rate is associatedwith a slice access rate that is greater than the slice demand rate.When the processing module selects the rebuilding priory scheme, themethod continues at step 926 where the processing module selects therebuilding rate of the set of rebuilding rates to be greater than therebuilding access demand rate. For example, the processing moduleselects the rebuilding rate to be just greater than a rebuilding rate ofthe scoring information. The method continues at step 930 where theprocessing module lowers the rebuilding rate when the estimated sliceaccess rate is not greater than a threshold. For example, the processingmodule determines the threshold based on a slice access demand rate anda minimum difference.

FIGS. 46A-B are diagrams illustrating examples 1000 and 1005 ofmodifying scoring information that includes scoring information at twotime frames. The scoring information includes an association of valuesof a set of rebuilding rates (RR), a set of slice access rates (SAR),and a set of scores (SCR) (e.g., score=((3*rebuild rate)+ slice accessrate)̂2). Initial scoring information is represented for a time frame 10and updated scoring information is represented for a subsequenttimeframe 11. The updating of the scoring information is updated inaccordance with a score updating scheme.

In particular, FIG. 46A represents an example 1000 when the scoringupdating scheme includes updating slice access rates and scores when anobserved slice access rate is greater than a previous observed sliceaccess rate for a given rebuilding rate. For example, for a rebuildingrate of 8 MB per second, the observed slice access rate is 79 fortimeframe T 11 and the previous observed slice access rate is 40 MB persecond at timeframe T 10. The entry for the slice access ratecorresponding to the rebuilding rate of 8 MB per second is updated from40 MB per second to 79 MB per second. Accordingly, the score is updatedas well from 4,096 to 10,609. The slice access rate entries forrebuilding rates of 6 MB per second and 4 MB per second are also updatedto 79 MB per second since corresponding slice access rates at timeframeT 10 were less than 79 MB per second. Accordingly, scores associatedwith the rebuilding rates of 4 MB per second and 6 MB per second of T 11are updated.

FIG. 46B represents another example 1005 when the scoring updatingscheme includes updating slice access rates and scores when the observedslice access rate is less than the previous observed slice access ratefor the given rebuilding rate. For example, for a rebuilding rate of 6MB per second, the observed slice access rate is 7 for timeframe T 11and the previous observed slice access rate is 50 MB per second attimeframe T 10. The entry for the slice access rate corresponding to therebuilding rate of 6 MB per second is updated from 50 MB per second to 7MB per second. Accordingly, the score is updated as well from 4,624 to625. The slice access rate entries for rebuilding rates of 8 MB persecond, 12 MB per second, and 16 MB per second are also updated to 7 MBper second since corresponding slice access rates at timeframe T 10 weregreater than 7 MB per second. Accordingly, scores associated with therebuilding rates of 8 MB per second, 12 MB per second, and 16 MB persecond of T 11 are updated. The method of operation is discussed ingreater detail with reference to FIG. 46C.

FIG. 46C is a flowchart illustrating an example of updating scoringinformation, which includes similar steps to FIG. 45C. The method beginswith step 1010 where a processing module (e.g., of a distributed storageand task (DST) integrity processing unit) monitors a slice access rateto produce an observed slice access rate for an associated rebuildingrate of a set of rebuilding rates and applies a learning function to theobserved slice access rate to produce an updated previous observed sliceaccess rate as shown in step 1012. When the updated observed sliceaccess rate is greater than the previous observed slice access rate forthe rebuilding rate, the method continues to step 1014 where theprocessing module updates any remaining previous observed slice accessrates that are lower than the updated previous observed slice accessrate and are associated with another rebuilding rate that is less thanthe rebuilding rate (e.g., FIG. 46A example). When the updated observedslice access rate is less than the previous observed slice access ratefor the rebuilding rate, the method continues at the step 1016 where theprocessing module updates any remaining previous observed slice accessrates that are greater than the updated previous observed slice accessrate and are associated with another rebuilding rate that is greaterthan the rebuilding rate (e.g., FIG. 46B example). The method continuesat step 1018 where the processing module updates a score associated withthe updated previous observed slice access rate.

FIG. 47A is a diagram illustrating another example 1100 of modifyingscoring information that includes scoring information at three timeframes. The scoring information includes an association of values of aset of rebuilding rates (RR), a set of slice access rates (SAR), and aset of scores (SCR). Initial scoring information is represented for atime frame T 20 and updated scoring information is represented forsubsequent timeframes T 21 and T 22. The updating of the scoringinformation is updated in accordance with a score updating scheme, wherea formula to generate the score may be updated for each timeframe basedon rebuilding activity. The rebuilding activity may include scanningstorage of encoded data slices to detect one or more storage errorsassociated with the encoded data slices. A measure of rebuildingactivity includes identifying when a particular DSNaddress rangeassociated with the encoded data slices has been scanned for sliceerrors. Periodic scanning for errors may be desired to quickly identifyand resolve slice errors. As time goes on, and a particular DSN addressrange has not been scanned for errors, the formula to generate the scoremay be updated to facilitate a more timely scanning for slice errors.

In particular, the scoring information at timeframe T 20 may includegenerating the scores using a formula of: score=((rebuildrate)̂2.5+(slice access rate)̂2.5). As such, similar priority is given toboth rebuilding (e.g., scanning) and slice access for routine reads andwrites of data. As time goes on, and the particular DSN address rangehas not been scanned, the scoring formula may be updated to a formulaof: score=((rebuild rate)̂3+(slice access rate)̂2). As such, for higherpriority is associated with rebuilding and lower priority is associatedwith slice access for the routine reads and writes of the data. As timegoes on, and the particular DSN address range has not been scanned, thescoring formula may be further updated to a formula of: score=((rebuildrate)̂3.5+ (slice access rate)̂1.5). As such, an even higher priority isassociated with rebuilding and an even lower priority is associated withslice access for the routine reads and writes of the data. Once theparticular DSN address range has been scanned, the scoring formula maybe returned back to the initial formula: score=((rebuild rate)̂2.5+(sliceaccess rate)̂2.5) when the similar priority is desired. The method ofoperation is discussed in greater detail with reference to FIG. 47B.

FIG. 47B is a flowchart illustrating another example of updating scoringinformation, which includes similar steps to FIG. 45C. The methodincludes step 1110 where a processing module (e.g., of a distributedstorage and task (DST) integrity processing unit) determines to updatescoring information that includes a set of rebuilding rates, a set ofslice access rates, and a corresponding set of scores. The determiningmay be based on one or more of a time frame has elapsed since a lastupdate, interpreting a schedule, receiving an error message, anddetecting that a rate of rebuilding is less than a desired rate ofrebuilding (e.g., rebuilding is falling behind).

The method continues at step 1112 where the processing module determineswhether a dispersed storage network (DSN) address range associated withthe scoring information has been scanned since a last scoringinformation update. The determining may be based on one or more ofreceiving an error message, interpreting a schedule, initiating a query,and receiving a query response. When the processing module determinesthat the DSN address range associated with the scoring information hasnot been scanned since the last scoring information update, the methodbranches to step 1116 where the processing module biases for rebuilding.When the processing module determines that the DSN address rangeassociated with the scoring information has been scanned since the lastscoring information update, the method continues to step 1114. Themethod continues at step 1114 where the processing module uses defaultsfor an updating scoring function. For example, the processing moduleresets exponents on rebuilding rate and on slice access rate to defaultswithin a scoring formula. The method branches to step 1118 where theprocessing module updates the set of scores.

When the processing module determines that the DSN address rangeassociated with the scoring information has not been scanned since thelast scoring information update, the method continues at step 1116 wherethe processing module biases the rebuilding in the updated scoringfunction. For example, the processing module raises an exponent on therebuilding rate and lowers the exponent on the slice access rate of thescoring formula.

The method continues at step 1118 where the processing module updates aset of scores based on the updated scoring function. For example, theprocessing module calculates the scoring formula on the set of scoresusing the updated scoring function. The method continues with steps1120, 1122 and 1124, which are similar to steps 916, 918 and 922 of FIG.45C where the processing module determines to update a rebuilding ratefor a storage unit, determine slice access demand rate and rebuildingaccess demand rate, and selects a rebuilding rate of the set ofrebuilding rates that is less than the rebuilding access demand rate andmaximizes a score associated with an expected slice access rate.

FIG. 48 is a flowchart illustrating another example of updating scoringinformation, that includes similar steps to FIGS. 45C and 47B. Themethod includes step 1210 where a processing module (e.g., of adistributed storage and task (DST) integrity processing unit) determinesto update scoring information that includes a set of rebuilding rates, aset of slice access rates, and a corresponding set of scores. The methodcontinues at step 1212 where the processing module determines a dataloss rate for a storage unit. The determining may be based on one ormore of receiving an error message, initiating a query, receiving aquery response, and measuring the data loss rate.

The method continues at step 1214 where the processing module determinesa measured data rebuilding rate for the storage unit. The determiningincludes at least one of interpreting a rebuilding schedule, initiatinga query, receiving a query response, and measuring the data rebuildingrate. The method continues at step 1216 where the processing moduledetermines an amount of data to rebuild for the storage unit based onthe data loss rate and the measured data rebuilding rate. Thedetermining includes calculating a difference between integrated dataloss rate over time and integrated measured data rebuilding rate overtime.

The method continues at step 1218 where the processing module determineswhether the amount of data to rebuild compares favorably to a rebuildingthreshold level. The determining includes indicating unfavorable whenthe amount of data to rebuild is greater than the rebuilding thresholdlevel. The method branches via decision block 1220 to step 1224 wherethe processing module biases for rebuilding when the amount of data torebuild compares unfavorably to the rebuilding threshold level. Themethod continues to step 1222 when the processing module determines thatthe amount of data to rebuild compares favorably to the rebuildingthreshold level. The method continues with step 1222 of FIG. 47B whenthe processing module determines that the amount of data to rebuildcompares favorably to the rebuilding threshold level where theprocessing module uses defaults for an updated scoring function.

The method continues with the 1224 and 1226 where the processing modulebiases for rebuilding in updated scoring function and updates a set ofscores of scoring information associated with a storage unit based onthe updated scoring function. The method continues with steps 1228, 1230and 1232 where the processing module determines to update a rebuildingrate for the storage unit, determines slice access demand rate andrebuilding access demand rate, and selects a rebuilding rate of the setof rebuilding rates that is less than the rebuilding access demand rateand maximizes a score associated with an expected slice access rate.

FIG. 49 is a flowchart illustrating another example of updating scoringinformation, which includes similar steps to FIG. 45C. The methodincludes step 1310 where a processing module (e.g., of a distributedstorage and task (DST) integrity processing unit), when detecting one ormore slice errors during rebuilding scanning, prioritizes completion ofthe rebuilding scanning for a dispersed storage network (DSN) addressrange over rebuilding one or more encoded data slices associated withthe one or more slice errors. The detecting includes scanning for sliceerrors within an allowed rebuilding rate. For each slice error of anencoded data slice, the method continues at step 1312 where theprocessing module identifies any other slice errors of other encodeddata slices where a set of encoded data slices includes the encoded dataslice and the other encoded data slices. The determining includesidentifying multiple errors per set of slices of a data segment (e.g.,more unreliable when more errors per set of encoded data slices areidentified).

For each data object, the method continues at step 1314 where theprocessing module determines a storage reliability level based onassociated one or more slice errors and corresponding other sliceerrors. The determining includes using a statistical model based onfailure rates and current rebuild rates. The method continues at step1316 where the processing module updates a set of scores based on thestorage reliability level, where scoring information includes the set ofscores, a set of rebuilding rates, and a set of slice access rates. Forexample, the processing module updates a scoring function to addemphasis to rebuilding when the reliability level is below a lowreliability level threshold. As another example, the processing modulereduces emphasis on rebuilding when the reliability level is above ahigh reliability level threshold. The method continues with steps 1318,1320 and 1322 where the processing module determines to update arebuilding rate for a storage unit, determine slice access demand rateand rebuilding access demand rate, and selects a rebuilding rate of theset of rebuilding rates that is less than the rebuilding access demandrate and maximizes a score associated with an expected slice accessrate.

It is noted that terminologies as may be used herein such as data, bitstream, stream, signal sequence, etc. (or their equivalents) have beenused interchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: encoding input data into a plurality ofslices; sending the plurality of slices to a first plurality ofdistributed storage and task execution units for storage, the firstplurality of distributed storage and task execution units being locatedat a corresponding first plurality of sites; receiving write slice datafrom the first plurality of distributed storage and task executionunits; determining when replication is to be applied to the plurality ofslices; when replication is to be applied to the plurality of slices:selecting a second plurality of distributed storage and task executionunits; generating a plurality of replicated slices corresponding to theplurality of slices; and sending the plurality of replicated slices tothe second plurality of distributed storage and task execution units. 2.The method of claim 1 wherein determining when replication is to beapplied to the plurality of slices is based on at least one of:analyzing the write slice responses, a requester identification, a dataidentification, a data type indication, a vault identification, and areplication mode predetermination.
 3. The method of claim 1 whereindetermining when replication is to be applied to the plurality of slicesincludes analyzing the write slice responses to determine when at leastone storage error occurred.
 4. The method of claim 1 wherein determiningwhen replication is to be applied to the plurality of slices includesanalyzing the write slice responses to determine a number of storageerrors and to determine when the number of storage errors comparesunfavorably to a replication threshold.
 5. The method of claim 1 whereindetermining when replication is to be applied to the plurality of slicesincludes analyzing the write slice responses to determine a number offavorable write slice responses and to determine when the number offavorable write slice responses compares unfavorably to a replicationthreshold.
 6. The method of claim 1 wherein the second plurality ofdistributed storage and task execution units are selected to correspondto at least one site that is disassociated with the first plurality ofsites.
 7. The method of claim 1 wherein the second plurality ofdistributed storage and task execution units are selected based on atleast one of: a predetermined selection, a column availability, areliability metric, a storage requirement associated with the pluralityof slices, and one or more sites associated with the second plurality ofdistributed storage and task execution units.
 8. A dispersed storage andtask (DST) processing unit comprises: at least one module, when operablewithin a computing device, that causes the computing device to: encodeinput data into a plurality of slices; send the plurality of slices to afirst plurality of distributed storage and task execution units forstorage, the first plurality of distributed storage and task executionunits being located at a corresponding first plurality of sites; receivewrite slice data from the first plurality of distributed storage andtask execution units; determine when replication is to be applied to theplurality of slices; when replication is to be applied to the pluralityof slices: select a second plurality of distributed storage and taskexecution units; generate a plurality of replicated slices correspondingto the plurality of slices; and send the plurality of replicated slicesto the second plurality of distributed storage and task execution units.9. The DST processing unit of claim 8 wherein determining whenreplication is to be applied to the plurality of slices is based on atleast one of: analyzing the write slice responses, a requesteridentification, a data identification, a data type indication, a vaultidentification, and a replication mode predetermination.
 10. The DSTprocessing unit of claim 8 wherein determining when replication is to beapplied to the plurality of slices includes analyzing the write sliceresponses to determine when at least one storage error occurred.
 11. TheDST processing unit of claim 8 wherein determining when replication isto be applied to the plurality of slices includes analyzing the writeslice responses to determine a number of storage errors and to determinewhen the number of storage errors compares unfavorably to a replicationthreshold.
 12. The DST processing unit of claim 8 wherein determiningwhen replication is to be applied to the plurality of slices includesanalyzing the write slice responses to determine a number of favorablewrite slice responses and to determine when the number of favorablewrite slice responses compares unfavorably to a replication threshold.13. The DST processing unit of claim 8 wherein the second plurality ofdistributed storage and task execution units are selected to correspondto at least one site that is disassociated with the first plurality ofsites.
 14. The DST processing unit of claim 8 wherein the secondplurality of distributed storage and task execution units are selectedbased on at least one of: a predetermined selection, a columnavailability, a reliability metric, a storage requirement associatedwith the plurality of slices, and one or more sites associated with thesecond plurality of distributed storage and task execution units.
 15. Acomputer readable storage medium comprises: at least one memory sectionthat stores operational instructions that, when executed by one or moreprocessing modules of one or more computing devices of a dispersedstorage network (DSN), causes the one or more computing devices to:encode input data into a plurality of slices; send the plurality ofslices to a first plurality of distributed storage and task executionunits for storage, the first plurality of distributed storage and taskexecution units being located at a corresponding first plurality ofsites; receive write slice data from the first plurality of distributedstorage and task execution units; determine when replication is to beapplied to the plurality of slices; when replication is to be applied tothe plurality of slices: select a second plurality of distributedstorage and task execution units; generate a plurality of replicatedslices corresponding to the plurality of slices; and send the pluralityof replicated slices to the second plurality of distributed storage andtask execution units.
 16. The computer readable storage medium of claim15 wherein determining when replication is to be applied to theplurality of slices is based on at least one of: analyzing the writeslice responses, a requester identification, a data identification, adata type indication, a vault identification, and a replication modepredetermination.
 17. The computer readable storage medium of claim 15wherein determining when replication is to be applied to the pluralityof slices includes analyzing the write slice responses to determine whenat least one storage error occurred.
 18. The computer readable storagemedium of claim 15 wherein determining when replication is to be appliedto the plurality of slices includes analyzing the write slice responsesto determine a number of storage errors and to determine when the numberof storage errors compares unfavorably to a replication threshold. 19.The computer readable storage medium of claim 15 wherein determiningwhen replication is to be applied to the plurality of slices includesanalyzing the write slice responses to determine a number of favorablewrite slice responses and to determine when the number of favorablewrite slice responses compares unfavorably to a replication threshold.20. The computer readable storage medium of claim 15 wherein the secondplurality of distributed storage and task execution units are selectedbased on at least one of: a predetermined selection, a columnavailability, a reliability metric, a storage requirement associatedwith the plurality of slices, and one or more sites associated with thesecond plurality of distributed storage and task execution units.